Classifications

• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q20/00—Payment architectures, schemes or protocols
  • G06Q20/08—Payment architectures
  • G06Q20/12—Payment architectures specially adapted for electronic shopping systems
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q20/00—Payment architectures, schemes or protocols
  • G06Q20/08—Payment architectures
  • G06Q20/10—Payment architectures specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q20/00—Payment architectures, schemes or protocols
  • G06Q20/22—Payment schemes or models
  • G06Q20/24—Credit schemes, i.e. "pay after"
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q20/00—Payment architectures, schemes or protocols
  • G06Q20/38—Payment protocols; Details thereof
  • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
  • G06Q20/401—Transaction verification
  • G06Q20/4016—Transaction verification involving fraud or risk level assessment in transaction processing
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q30/00—Commerce
  • G06Q30/04—Billing or invoicing

Definitions

• Embodiments of the invention relate generally to the field of financial transaction processing. More specifically, embodiments of the invention relate to systems and methods for pricing presentation instrument transaction processing.
• a typical credit card transaction proceeds by extracting account information from the credit card, typically using a point of sale device at a merchant location, and submitting the account information along with a requested payment amount to a processing system.
• a processing system may involve the merchant's bank, a credit card association and associated processing network, such as the VISA® network or the MASTERCARD® network, and/or the issuer's bank, as is known in the art.
• a merchant in order to process a credit card transaction, a merchant typically establishes an account with a processing organization. Because the processing organization takes on certain financial risks when agreeing to process a merchant's transactions, an application and underwriting process typically takes place before an account is opened. For example, an account maybe established by first requiring the merchant to fill out a credit application. The credit application is then sent to an underwriter who reviews information in the application to determine whether the merchant would be a suitable client. If so, the account is established, and the merchant may begin accepting at least certain types of credit cards as payment for their goods or services.
• Embodiments of the invention provide a method of processing a presentation instrument transaction for a merchant.
• the method includes, at a host computer system, receiving transaction information from the merchant for a presentation instrument transaction to process.
• the transaction information includes a ticket amount.
• the method also includes, at the host computer system, determining a settlement amount to pay the merchant for the transaction.
• the settlement amount is less than the ticket amount and the difference between the ticket amount and the settlement amount is based, at least in part, on a fee.
• the method further includes remitting a payment to the merchant.
• the payment includes the settlement amount.
• the method also includes further processing the transaction to thereby obtain reimbursement.
• the fee is determined, at least in part, by calculating an expected loss specific to the merchant.
• the expected loss is based, at least in part, on a probability of default specific to the merchant and a gross exposure specific to the merchant.
• the presentation instrument transaction may be based on a presentation instrument such as a credit card, gift card, stored value card, or
• the method includes calculating the probability of default specific to the merchant as a function of a merchant risk score specific to the merchant.
• the merchant risk score includes a weighted summation of one or more attributes that may include: 12 month Chargeback percent; Ratio of 30 day Credit percent to 180 day Credit percent; # of 60+ Trade lines in 24 months; 30 day Keyed sales $; Number of Recurring Sales over 12 Months; Ratio of total balance to high credit/credit limit for all bank revolving accounts; Ratio of 30 day Chargeback percent to 180 day Chargeback percent; 12 month Credit percent (12 month Credit $ / 12 month Sales $); Ratio of number of declined Authorizations over 12 months to number of sales over 12 months; and Number of trade lines.
• the probability of default may be derived from the merchant risk score using a lookup table.
• the gross exposure specific to the merchant may be determined, at least in part, as a function of undelivered goods or services for which the merchant has been paid.
• the fee may be further determined, at least in part, by calculating a contribution specific to the merchant, wherein the contribution comprises a difference between revenue generated from the merchant and expenses attributable to the merchant.
• the fee may be further determined, at least in part, by determining a risk adjusted contribution specific to the merchant.
• the risk adjusted contribution is based, at least in part, on the contribution and the expected loss.
• a method of determining a fee to charge a merchant for processing presentation instrument transactions for the merchant includes, over a period of time, processing presentation instrument transactions for the merchant. Each transaction may include transaction information. The method also includes, at a host computer system, collecting the transaction information, at the host computer system, using the transaction information, at least in part, to calculate an expected loss specific to the merchant. The expected loss may be based, at least in part, on a probability of default specific to the merchant and a gross exposure specific to the merchant. The method also includes using the expected loss to determine a fee to charge the merchant for processing the merchant's future presentation instrument transactions and, thereafter, charging the merchant the fee to process a new presentation instrument transaction.
• the new presentation instrument transaction is based on a presentation instrument which may be a credit card, gift card, stored value card, or debit card.
• the probability of default may be derived from the merchant risk score using a lookup table.
• the gross exposure specific to the merchant may be determined, at least in part, as a function of undelivered goods or services for which the merchant has been paid.
• the method may include calculating a contribution specific to the merchant.
• the contribution may be a difference between revenue generated from the merchant and expenses attributable to the merchant.
• the method also may include calculating a risk adjusted contribution based, at least in part, on the contribution and the expected loss and using risk adjusted contribution, at least in part, to determine the fee.
• a presentation instrument transaction processing system includes a host computer system and computer-executable instructions that program the host computer system to receive transaction information from a merchant for a presentation instrument transaction to process.
• the transaction information may include a ticket amount.
• the computer-executable instructions also program the host computer system to determining a settlement amount to pay the merchant for the transaction.
• the settlement amount is less than the ticket amount and the difference between the ticket amount and the settlement amount is based, at least in part, on a fee.
• the computer-executable instructions also program the host computer system to initiate a process to remit a payment to the merchant.
• the payment includes the settlement amount.
• the computer-executable instructions also program the host computer system to further process the transaction to thereby obtain reimbursement.
• the computer-executable instructions further program the host computer system to determine the fee, at least in part, by programming the host computer system to calculate an expected loss specific to the merchant.
• the expected loss is based, at least in part, on a probability of default specific to the merchant and a gross exposure specific to the merchant.
• the presentation instrument transaction may be based on a presentation instrument such as a credit card, gift card, stored value card, or debit card.
• the computer-executable instructions further program the host computer system to calculate the gross exposure specific to the merchant, at least in part, as a function of undelivered goods or services for which the merchant has been paid.
• the computer-executable instructions may further program the host computer system to determine the fee, at least in part, by calculating a contribution specific to the merchant, wherein the contribution comprises a difference between revenue generated from the merchant and expenses attributable to the merchant.
• the computer-executable instructions may further program the host computer system to determine the fee, at least in part, by calculating a risk adjusted contribution specific to the merchant, wherein the risk adjusted contribution is based, at least in part, on the contribution and the expected loss.
• FIG. 1 illustrates an exemplary system according to embodiments of the invention.
• FIG. 2 illustrates an exemplary method according to embodiments of the invention, which method may be embodied in the system of Fig. 1.
• FIG. 3 illustrates an exemplary method for determining a merchant's Risk- Adjusted Contribution, according to embodiments of the invention.
• Embodiments of the present invention provide systems and methods for setting or resetting the fees (i.e., pricing and re-pricing) presentation instrument processing organizations charge merchants for the service.
• the fee is set such that it accounts for the processing organization's expected loss if the merchant were to go out of business or otherwise default on its credit or business obligations.
• This detailed description presents the invention in a non-limiting example relating to credit card processing organizations.
• Other embodiments include processing other types of presentation instruments, including, for example, debit cards, gift cards, stored value cards, and the like.
• the application process includes an underwriting process wherein the credit processing organization estimates the degree of credit risk exposure.
• Credit risk exposure may result from a number of factors.
• the method by which a merchant obtains a customer's account number may introduce a degree of exposure.
• In-person sales using a point of sale device generally introduce less risk than other transaction methods. This is so for a variety of reasons, including, for example: the merchant is able to verify certain information about the customer presenting the credit card as payment; the transaction is posted immediately; and the customer acknowledges the transaction by signing a receipt.
• mail order and telephone order transactions wherein account information is given over the phone or through the mail, eliminate many of the safeguards inherent to in-person transactions. This is also the case with Internet sales.
• the credit card processing organization may become exposed to greater risk, especially between the time that the merchant is paid and the time that payment is received from the customer.
• Another factor that may affect credit risk exposure is the number of days between the transaction and the delivery of the product or service. For example, a merchant who accepts credit card payments for meals at a restaurant does not generate the degree of credit risk as does a merchant providing travel services booked months in advance. The risk varies as well in relationship to the frequency with which a merchant delivers a product or service according to a particular delivery schedule considered to be an industry average.
• One method for categorizing merchants according to credit risk is by industry.
• SIC code system or Standardized Industrial Classification code system
• credit processing organizations may compare merchants with other merchants according to their SIC code. Because merchants within a particular SIC code tend to have similar percentages of mail order and telephone order sales and similar delivery times and patterns, the credit risk associated with merchants in a particular SIC code tends to be similar.
• credit processing organizations use industry-specific criteria in the credit underwriting process.
• the processing organization places a point-of-sale device at the merchant's business location(s) or otherwise provides the merchant the ability to transfer transaction details to the processor.
• the details minimally include the customer's account identifier and the amount of the transaction (a.k.a., "ticket amount”).
• the processor credits a portion of the transaction amount (a.k.a., "settlement amount") to the merchant's bank account and initiates the process of obtaining funds from the customer.
• the processor typically withholds a portion of the transaction amount as compensation for processing the transaction.
• the amount withheld may be a percentage of the transaction amount, a flat fee, a percentage of a total volume processed for the merchant, or the like.
• the amount includes the expected loss allocable to the merchant.
• “Expected loss” is a statistical term derived from the more commonly-known term “expectation.” Mathematically, expectation is a summation of the probability of each possible outcome of an event multiplied by the consequences of each outcome. For example, wagering $1 on the flip of a true coin (i.e., statically perfect in that heads should occur with the same frequency as tails in the long run) has a zero expectation per event, since 50% of the time you will win $1 and 50% of the time you will lose $1. If, however, you were to find someone to pay you $2 for each time the coin comes up heads in exchange for $1 each time the coin comes up tails, then your expectation is $0.50 per event (($2 x 50%) + (-$1 x 50%)). "Expected loss” then is the negative return portion of the equation.
• expected loss may account for any event that would cause the processor to lose money in the merchant relationship.
• the merchant may go out of business, in which case, the processor could lose money for any undelivered goods or services for which customers paid with a presentation instrument.
• the processor may have already paid the merchant for the transaction but will be unable to collect from the merchant's customers or will have to refund the customers' money who never received the benefit of the transaction.
• the merchant may change processors, in which case the processor may not receive unamortized setup costs for the merchant or otherwise lose money as a result of the attrition. Many such examples are possible.
• the expected loss may be incorporated into the fee the processor charges the merchant for the processing service.
• a specific merchant's transaction processing fee may be a true reflection of the expected loss allocable to the merchant.
• the expected loss calculation may be based on the merchant's recent history with the processor, in the case of continuing merchants, the merchant's history with another processor, in the case of newly enrolled merchants, or other factors such as the merchant's credit history, business classification, sales volume, delivery schedule, and/or the like. This represents a significant improvement over pricing methodologies that simply categorize merchants into risk groups and price them accordingly.
• a Merchant Risk Score is calculated based on measurable data specific to the merchant. If the data are not available (e.g., the merchant is newly acquired, has changed businesses, etc), the MRS may be based on expected ranges of the data, the merchant's history with another processor, a credit report on the business owner, a credit report on the business entity, and the like. If the data are estimated, the merchant may be re-scored - and possibly re-priced - after a statistically- significant quantity of data has been collected.
• the data may be any of a variety of attributes, which may be weighted in the calculation of the score. Attributes include, for example, 12 month chargeback percentage, a ratio of total balance to high credit/credit limit for all bank revolving accounts, the number of trades 60 days or more delinquent in 24 months, 12 month declines authorization number/12 month sales number, and/or the like, as will be explained in more detail hereinafter.
• a Probability of Default (Pd) niay be calculated as a function of the MRS.
• the specific function that converts MRS to P d may change over time, based on experience.
• the function may be linear, or may include other variables or terms that relate the two.
• the P d is extracted from a lookup table that relates the two.
• the Pd is then used to calculate an Expected Loss (EL) by applying the P d to the Gross Exposure (GE) relating to the merchant.
• the GE is a measure of the loss the processor would experience if the merchant defaulted. It may be an average over a period of time (e.g., one year, one month, the merchant's longevity, etc.) and may be sampled at any frequency (e.g., daily, weekly, monthly, etc.).
• the GE may include, for example, the total volume of undelivered goods and/or services, a fraction of total volume to account for charge backs, a fraction of total volume to account for disputes, and/or the like.
• the EL is then used to adjust the profit derived from the merchant (Revenue — Expenses), to produce a Risk- Adjusted Contribution (RAC) from the merchant.
• RAC Risk- Adjusted Contribution
• the merchant may be re-priced. That is, the fee may be adjusted so that the revenue term results in the desired RAC.
• the fee may be adjusted based on expected revenue to produce the desired RAC, and the merchant may be monitored going forward and re-priced accordingly.
• a software routine may be set up to periodically (e.g., daily) extract the necessary variables from a database of transaction information associated with a mainframe that processes transactions.
• the previously-described calculations maybe performed on the data to calculate the merchant's RAC. Allowed fluctuations may be predetermined so that only deviations outside the range will be flagged to an exceptions file for further evaluation by an underwriter, clerk, or the like.
• the MRS is calculated on a different periodic (e.g., monthly) schedule than the RAC (e.g., yearly). Each can be compared to allowed deviations so that exception management is applied to deal only with excessive deviations.
• the entire process is automated, including measures such as sending a letter 30 days in advance of a planned fee adjustment, with actual implementation thereafter.
• Ratio of total balance to high credit/credit limit for all bank revolving accounts (br34) 7. Ratio of 30 day Chargeback percent to 180 day Chargeback percent (cb7)
• Temp 2.6499 + weight_at ⁇ l + weight_vl ⁇ l + weight_v25 + weight_cb7 + weight__br34 + weight_v59 + weight_vl84 + weight_gO66 + weight_cdl2 + weight_vl22.
• P 1 / (1+ exp(-Temp) ).
• the system 100 includes a server computer 102 (a.k.a., "host computer system") connected to a network 104.
• the server computer 102 may be any of a number of computing devices known to those skilled in the art, such as, for example, a personal computer, a workstation, or the like.
• Application programs residing on the server computer 102 allow the server computer to send and receive files from other computing devices.
• a suitable interface as is known in the art, allows the server computer 102 to communicate with other devices via the network 104.
• the network 104 may be, for example, a wide area network, a local area network, the Internet, or the like.
• the server computer 102 is configured to receive merchant credit transaction information from one or more point of sale deices 106 or credit processing computers 108. Exemplary point-of-sale devices are described in U.S. Patent No. 6,547,132.
• the server computer 102 causes the transaction information to be stored on a data storage arrangement.
• the data storage arrangement, or database 110 may be any one or a combination of well- known types of recording media, including, for example, magnetic tape, disk drives, optical storage systems and the like.
• the database 110 may be integral to the server computer 102 or located elsewhere such that the server computer 102 accesses the database 110 via a network.
• the server computer 102 is able to exchange information with one or more credit risk assessment computers 112.
• the risk assessment computer 112 periodically requests necessary data from the server computer 102 to calculate MRS, EL, and/or RAC for one or more merchants. If the calculations fall outside of predetermined ranges or deviate more than a predetermined amount from prior calculations for specific merchants, then the exceptions may be flagged for further processing, either manually or automatically.
• the server computer 102 and/or the credit risk assessment computer 112 may be configured more specifically to perform the methods of the present invention. It merits noting that in some embodiments of the present invention, the server computer 102, the credit risk assessment computer 112 and the database 110 exist together in a single computing device.
• Fig. 2 illustrates a method 200 of pricing or re- pricing presentation instrument transaction processing.
• the method may be embodied in the system of Fig. 1, or other appropriate system.
• the method 200 is merely exemplary and that other methods according to other embodiments may have more, fewer, or different steps than those illustrated and described herein. Further, other methods according to other embodiments may traverse the steps illustrated and described herein in different orders.
• the method begins at block 202 at which point a merchant is set up as a presentation instrument transaction processing client. Doing so may include taking an application, underwriting the application, establishing a fee, installing any necessary hardware, and/or the like.
• the underwriting process may be accomplished according to the teachings of previously-incorporated United States Patent Application No. 10/109,198, entitled “MERCHANT APPLICATION AND UNDERWRITING SYSTEMS AND METHODS” and/or previously-incorporated United States Patent Application No. 10/108,934, entitled “MERCHANT ACTIVATION TRACKING SYSTEMS AND
• METHODS Establishing the fee may be accomplished according to the teachings herein, to be described more fully with reference to Fig. 3, in which certain unknown variables are estimated.
• Transaction processing includes receiving transaction information from the merchant, reimbursing the merchant for the transaction amount, less a fee, storing the transaction data for later evaluation, and collecting from the merchant's customer.
• the merchant is periodically evaluated. This may include calculating a Merchant Risk Score (MRS) for the merchant, calculating the merchant's Expected Loss (EL), calculating the Merchant's Risk- Adjusted Contribution (RAC), reviewing key variables in any of the foregoing factors, and/or the like.
• MRS Merchant Risk Score
• EL Expected Loss
• RAC Merchant's Risk- Adjusted Contribution
• the evaluation may be accomplished daily, weekly, monthly, annually, or on any useful frequency.
• the process includes extracting the necessary information from the database 110 of Fig. 1 and performing the appropriate calculations at the risk assessment computer 112 of Fig. 1.
• the result(s) are evaluated at block 208 to determine if the merchant should be flagged as an exception.
• the merchant may be flagged based on a factor being out of a specific range, above or below predetermined thresholds, outside a predetermined deviation from a prior calculation, and/or the like. Further, the threshold(s), ranges, and acceptable deviations may be unique to each factor (i.e., a different threshold for MRS than RAC) and/or each evaluation frequency. If the merchant is not flagged, the process loops back to block 204. [0042] If the merchant is flagged, the merchant may be evaluated in detail at block 210.
• the detailed evaluation may include calculating additional factors, reviewing the merchant's history for the presence on anomalous events, contacting the merchant, and/or the like. Conveniently, the process may be facilitated through the use of a decision tree. Decision trees are more fully explained in previously-incorporated United States Patent Application No. 10/108,781, entitled “DECISION TREE SYSTEMS AND METHODS". This may allow the processing organization to substantially reduce the cost of labor for performing such evaluations by employing less skilled administrative personnel to accomplish tasks typically reserved to analysts or underwriters.
• Fig 3 illustrates a method 300 of accomplishing the computational portion of the method 200 in greater detail.
• the method 300 is merely exemplary, and other methods according to other embodiments may have more, fewer, or different steps than those illustrated and described herein. Further, other methods according to other embodiments may traverse the steps illustrated and described herein in different orders.
• the method 300 may be embodied in the system 100 of Fig. 1 or other appropriate system. Further, the individual steps of the method 300 maybe distributed among two or more of the steps illustrated and described with respect to Fig. 2, rather than being all performed within one of the steps, which may be the case.
• the method 300 begins by calculating the Merchant's Risk Score (MRS) at block 302.
• MRS Merchant's Risk Score
• the MRS is calculated by weighting any of a number of factors and combining them to produce the score.
• the factors maybe subjected to a range, such that there is a minimum and maximum possible contribution from each factor. In a specific embodiment, the factors combine to produce a number in the range 0 to 999.
• the MRS is converted to a Probability of Default (P d ) at block 304.
• the P d may have a linear relationship to the MRS, may be an output from a lookup table using the MRS as an input, or the like.
• the formula, function, table, or the like used to determine P d from MRS may change over time based on how accurately history reflects reality, the objective being to predict future losses as accurately as possible.
• the gross exposure relating to the merchant is determined based on the merchant's actual processing history.
• the merchant's gross exposure typically is not a statistical number; it is an accurate reflection of the amount of money the processor would lose if the merchant were to default. While the GE may be an average over a given time based on a particular sampling frequency, it is not typically an estimate based on predictions for the merchant specifically or a larger population. GE may include the average gross volume of undelivered goods or services, an average of charge backs over a specific time, an average of disputes resolved against the merchant over time, and/or the like. Other GE calculations may include other factors, some of which may be statistical approximations.
• the Expected Loss (EL) attributable to the merchant may be determined. This is accomplished in this embodiments by simply multiplying the two factors at block 308.
• the contribution (i.e., profit) derived from the merchant is calculated by subtracting from the revenue derived from the merchant the expenses associated with processing the merchant's transactions and maintaining the merchant as a client. This term may be based on a specific time frame, which should be the same time frame used for calculating other terms. From this result, a Risk- Adjusted Contribution (RAC) is calculated by subtracting the EL attributable to the merchant from the merchant's contribution.
• RAC Risk- Adjusted Contribution

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